Pulse oximeters are devices used to measure oxygen saturation level (SpO2) in the blood. Conventional pulse oximeters perform photoplethysmography (PPG) to measure SpO2. Photoplethysmography (PPG) is the electro-optic technique of measuring the cardiovascular pulse wave found throughout the human body. This pulse wave is caused by the periodic pulsations of arterial blood volume and is measured by the changing optical absorption. The measurement system consists of a light source, a photo-detector, a signal recovery, a processor, and a display system. These PPG devices differentiate between light absorption due to blood volume and that of other fluid and tissue constituents by observation that arterial blood flow pulsates while tissue absorption remains static. The PPG device measurements are non-invasive and can be applied to blood bearing tissue to conduct heart and respiration rate monitoring, to perform blood pressure studies, and to determine blood hemoglobin oxygen saturation.
Existing PPG devices have substantial disadvantages, however. The PPG device measurements are sensitive to corruption from external dynamics, causing motion artifacts that degrade the signal-to-noise ratio. An artifact may include unwanted signals superimposed onto the PPG signal, which can be induced by any external dynamics. For example, variation in the optical coupling between the probe head and the patient, possibly induced by patient movement, may cause an artifact. Motion artifacts can render it substantially difficult for the oximeter to accurately determine the patient's PPG signal, therefore causing errors in the pulse rate and oxygen saturation outputs.
Another limitation is that PPG relies on AC photo-plethysmogram (PPG) component, which is synchronous with cardiac pulsations but very small compared to the overall DC component, to determine SpO2. Because the AC component is small relative to the DC component, accurate measurement of the AC component is difficult. Inaccuracies in AC component measurements cause inaccuracies in SpO2 measurements because oximeters compute SpO2 using the relative magnitudes of the AC components of the different optical photo-plethysmograms. In addition, in poorly perfused patients, the circulation may not adequately modulate the light beams to the point where it is difficult to distinguish the synchronous cardiac pulsations from system noise. Thus, the usefulness of most commercial pulse oximeters is limited to situations in which patient is well perfused and subject to minimal motion.
Many pulse oximeters utilize time-domain algorithms that determine the period and amplitude of the photo-plethysmograms. These techniques typically analyze time-domain parameters such as slope transition, minima, maxima, and rise and fall time. Additionally, such algorithms may employ decision rules in order to reject data, which falls outside of certain limits.
A difficulty with these time-domain algorithms is that the SpO2 is conventionally averaged with several recent values in order to reduce the disruptive effect of corrupted data. Such averaging is only useful if the number of bad values is small relative to the number of good data values.
Several advanced technology pulse oximeters have been introduced that utilize digital signal processing in the frequency domain as a solution to some scenarios presented by the cases where artifacts are induced.
An existing technique utilizes saturation-based digital signal processing algorithms. The patent is directed toward a signal processor which acquires a first signal, including a first desired signal portion and a first undesired signal portion, and a second signal, including a second desired signal portion and a second undesired signal portion, wherein the first and second desired signal portions are correlated. The signals may be acquired by propagating energy through a medium and measuring an attenuated signal after transmission or reflection. Alternatively, the signals may be acquired by measuring energy generated by the medium. A processor generates a noise reference signal which is a combination of only the undesired signal portions and is correlated to both the first and second undesired signal portions. The noise reference signal is then used to remove the undesired portion of each of the first and second measured signals via an adaptive noise canceller, preferably of the joint process estimator type. The processor may be employed in conjunction with an adaptive noise canceller in physiological monitors wherein the know properties of energy attenuation through a medium are used to determine physiological characteristics of the medium.
An underlying assumption in the '642 patent is that all motion artifacts come from the movement of lower-saturation venous blood. Furthermore, this motion artifact results in correlated red and infrared signals. A limitation with this algorithm is that when red and infrared signals become corrupted by sources other than moving arterial and venous blood, such as sensor movement relative to skin, the artifact can result in uncorrelated red and infrared signals. Thus this method has the potential to pick and choose for display a false high saturation created by non-venous artifact.
An existing technique involving a frequency domain approach utilizes a cardiac-based digital filtering algorithm. This Kalman filtering algorithm minimizes chaotic random signal artifact, regardless of the red and infrared correlation. One drawback of this cardiac-based filtering is the assumption that, on average and over several seconds of time, signal noise coming from real patient motion and other sources does not occur at the heart rate. As a result, the filters associated with this approach assume that noise is chaotic and random and in turn tend to find the underlying cardiac signal that is mixed with noise created by patient movement or other sources of artifact.
Another existing approach involves an oximeter having two light emitting diodes (LEDs), a red LED and an infrared LED, that alternatively illuminate an intravascular blood sample with two wavelengths of electromagnetic radiation. The electromagnetic radiation interacts with the blood and a residual optical signal is both reflected and transmitted by the blood. A photodiode in the light-to-frequency converter (LFC) collects oximetry data from the intravascular blood sample illuminated by the two LEDs. The LFC produces a periodic electrical signal in the form of a pulse train having a frequency, the logarithm of which is in linear relationship to the logarithm of the intensity of the optical signal received by the LFC. The data becomes an input to a high-speed digital counter, which converts the pulsatile signal into a form suitable to be entered into a central processing unit (CPU) of a computer system. Once inside the CPU, the time-domain data is converted into the frequency domain by, for example, performing the well-known Fast Fourier Transform (FFT) on the time-domain data. The frequency domain data is then processed to determine the saturation value.
In this approach, the magnitudes of the AC and DC components for both the red LED and the IR LED are determined using a frequency domain analysis. For both the red and infrared signals, the AC component is determined by the magnitude of the highest spectral peak found between 0.5 to 2.5 Hz. This highest peak represents the pulsatile, or AC component, of the oximetry waveform. Likewise, the magnitude of the DC component is the highest spectral peak generally found in the first bin at 0 Hz.
Another approach involves a system for processing signals containing information about the pulse rate and oxygen saturation of arterial blood flowing in tissue. To determine the pulse rate and oxygen saturation from the signals, the positive peaks, negative peaks, and period of the signal are determined. The disclosed invention accomplishes this by first searching for a sustained positive sloping region of the signal. Then the first derivative of the signal with respect to time is analyzed and points on the signal before and after the occurrence of a slope reversal are marked. If the slope at the first point is positive, the interval between the two points is searched for a maximum amplitude that is identified as a positive peak. After the occurrence of a negative sloping region of the signal, another pair of points are marked occurring before and after a subsequent slope reversal. The minimum amplitude of the signal between these points is then identified as a negative peak. These positive and negative peaks are then compared with waveform templates to determine whether the amplitude between the peaks falls within an allowable range and to determine whether the interval between the peaks likewise falls within an acceptable range. These ranges are adjustable in proportion to the amplitude and interval compared against them. In this manner, values for the positive peak, negative peak, and period of the signal can be determined.
Preferably, the output produced by the above-described derivative processor is the auto-normalized convolution derivative. This auto-normalization provides sufficient processing to discriminate peaks from inflections in the PPG, provided that the signal is a well-behaved function. In practice, physiological signals such as the PPG are not well behaved and are often modulated with artifacts due to noise, interference, and patient motion.
Another approach involves an ECG-synchronized pulse oximeter. The patent discloses a pulse oximeter, including a sensor for the emission and detection of two beams of light of different wavelengths. The beams are passed through skin tissue and modulated by the flow of blood therein. The preferred embodiment includes an apparatus for the amplification and detection of an ECG, R-wave signal. This signal is used as a reference to guide the averaging of subsequent optical pulse waveforms. The weight given to the newest pulse waveform during the averaging process is determined by the amplitude of that pulse waveform and by the degree of similarity between it and the preceding pulse waveform. The composite, averaged pulse waveform is then used in computing the oxygen saturation of the blood.
In light of the above-described disadvantages, there is need for methods and systems that remove asynchronous motion signals from synchronous cardiac signals superimposed in the photo-plethysmogram. Additionally, there is a need for a system that processes photo-plethysmographic signals in both time and frequency domains. Furthermore, there is a need for a system to generate a unique ‘cardiac’ morphology, which helps in separating cardiac signals from motion signals.